Liquidation Strategy📈 It enters a long trade when long liquidation spikes above a set threshold.
📉 It enters a short trade when short liquidation drops below the negative threshold.
🧮 It optionally filters entries using an EMA multiplier.
🔁 It exits long when RSI crosses below its smoothed version.
🔄 It exits short when RSI crosses above its smoothed version.
🔗 It requires linking to the Liquidations indicator on Bybit or OKX charts.
震盪指標
Chimera [theUltimator5]In myth, the chimera is an “impossible” hybrid—lion, goat, and serpent fused into one—striking to look at and formidable in presence. The word has come to mean a beautiful, improbable union of parts that shouldn’t work together, yet do.
Chimera is a dual-mode market context tool that blends a multi-input oscillator with classic ADX/DI trend strength, plus optional multi-timeframe “gap-line” tracking. Use it to visualize regime (trend vs. range), momentum swings around an adaptive midline, and higher timeframe (HTF) reference levels that auto-terminate on touch/cross.
Modes
1) Oscillator view
A smoothed composite of five common inputs—RSI, MACD (oscillator), Bollinger position, Stochastic, and an ATR/DI-weighted bias. Each is normalized to a comparable 0–100 style scale, averaged, and plotted as a candle-style oscillator (short vs. long smoothing, wickless for clarity). A dynamic midline with standard-deviation bands frames neutral → bearish/bullish zones. Colors ramp from neutral to your chosen Oversold/Overbought endpoints; consolidation can override to white.
Here is a description of the (5) signals used to calculate the sentiment oscillator:
RSI (14): Measures recent momentum by comparing average gains vs. losses. High = strength after advances; low = weakness after declines. (Z-score normalized to 0–100.)
MACD oscillator (12/26/9): Uses the difference between MACD and its signal (histogram) to gauge momentum shifts. Positive = bullish tilt; negative = bearish. (Z-score normalized.)
Bollinger Bands position (20, 2): Locates price within the bands (0–100 from lower → upper). Near upper suggests strength/expansion; near lower suggests weakness/contraction. (Then normalized.)
Stochastic (14, 3, 3): Shows where the close sits within the recent high-low range, smoothed via %D. Higher values = closes near highs; lower = near lows. (Scaled 0–100.)
ATR/DI composite (14): Volatility-weighted directional bias: (+DI − −DI) amplified by ATR as a % of price and its relative average. Positive = bullish pressure with volatility; negative = bearish. (Rank/scale normalized.)
All five are normalized and averaged into one composite, then smoothed (short/long) and compared to an adaptive midline with bands.
2) ADX view
Shows ADX, +DI, –DI with user-defined High Threshold. Transparency and color shift with regime. When ADX is strong, a directional “fire/ice” gradient fills the area between ADX and the high threshold, biased toward the dominant DI; when ADX is weak, a soft white fade highlights low-trend conditions.
HTF gap-line tracking (optional; both modes)
Detects “gap-like” reference levels after weak-trend consolidation flips into a sudden DI jump.
Anchors a line at the event bar’s open and auto-terminates upon first touch/cross (tick-size tolerance).
Auto-selects up to three higher timeframes suited to your chart resolution and prints non-overlapping lines with labels like 1H / 4H / 1D. Lower-priority duplicates are suppressed to reduce clutter.
Confirmation / repaint notes
Signals and lines finalize on bar close of the relevant timeframe.
HTF elements update only on the HTF bar close. During a forming bar they may appear transiently.
Line removal finalizes after the bar that produced the touch/cross closes.
Visual cues & effects
Oscillator candles: Open/High = long smoothing; Low/Close = short smoothing (no wicks).
Adaptive bands: Midline ± StdDev Multiplier × stdev of the blended series.
Consolidation tint: Optional white backdrop/candles when the consolidation condition is true (balance + low ADX).
Breakout VFX (optional): With strong DI/ADX and Bollinger breaks, renders a subtle “fire” flare above upper-band thrusts or “ice” shelf below lower-band thrusts.
Inputs (high-level)
Visual Style: Oscillator or ADX.
General (Oscillator): Lookback Period, Short/Long Smoothing, Standard Deviation Multiplier.
Color (Oscillator): Oversold/Overbought colors for gradient endpoints.
Plot (Oscillator): Show Candles, Show Slow MA Line, Show Individual Component (RSI/MACD/BB/Stoch/ATR).
Table (Oscillator): Show Information Table & position (compact dashboard of component values + status).
ADX / Gaps / VFX (both modes): ADX High Threshold, Highlight Backgrounds, Show Gap Labels, Visual Overlay Effects, and color choices for current-TF & HTF lines.
HTF selection: Automatic ladder (3 tiers) based on your chart timeframe.
Alerts (built-in)
Buy Signal – Primary: Oscillator exits oversold.
Sell Signal – Primary: Oscillator exits overbought.
Gap Fill Line Created (Any TF)
Gap Fill Line Terminated (Any TF)
ADX Crossed ABOVE/BELOW Low Threshold
ADX Crossed ABOVE/BELOW High Threshold
Consolidation Started
Alerts evaluate on the close of the relevant timeframe.
How to read it (quick guide)
Pick your lens: Oscillator for blended momentum around an adaptive midline; ADX for trend strength and DI skew.
Watch extremes & mean re-entries (Oscillator): Approaches to the top/bottom band show persistent momentum; returns toward the midline show normalization.
Check regime (ADX): Below Low = low-trend; above High = strong trend, with “fire/ice” bias toward +DI/–DI.
Track gap lines: Fresh labels mark new reference levels; lines auto-remove on first interaction. HTF lines add context but finalize only on HTF close.
The uniqueness from this indicator comes from multiple areas:
1. A unique multi-timeframe algorithm detects gap fill zones and plots them on the chart.
2. Visual effects for both visual modes were hand crafted to provide a visually stunning and intuitive interface.
3. The algorithm to determine sentiment uses a unique blend of weight and sensitivity adjustment to create a plot with elastic upper and lower bounds based off historical volatility and price action.
[DEM] Relative Strength Signal (With Backtesting) Relative Strength Signal (With Backtesting) is a momentum indicator that generates trading signals based on when an asset reaches its highest or lowest relative strength compared to the SPY benchmark over a 20-period lookback window. The indicator calculates relative strength by dividing the current asset's price by SPY's price, then triggers buy signals when this ratio hits a 20-period high (indicating maximum outperformance) and sell signals when it reaches a 20-period low (indicating maximum underperformance). To prevent signal clustering and improve practical utility, the indicator includes a built-in filter that requires a minimum number of bars (default 20) to pass between signals of the same type, ensuring adequate spacing for meaningful trade opportunities. The system includes comprehensive backtesting functionality that tracks signal accuracy, average returns, and signal frequency over time, displaying these performance metrics in a detailed statistics table to help traders evaluate the effectiveness of trading on relative strength extremes versus the broader market.
[DEM] Multiple Linear Regression Score Multiple Linear Regression Score is a composite momentum indicator that evaluates market conditions by analyzing a reference symbol (defaulting to NDX) across multiple technical dimensions and combining them into a single predictive score. The indicator processes ten different technical variables including RSI, MACD components (line, signal, and histogram), price relationships to various moving averages (10, 50, 100, 200), and short-term price changes (1-day and 5-day), converting most into binary signals (1 or 0) based on whether they're above or below zero. These binary and continuous inputs are then weighted using regression-derived coefficients and combined into a final percentage score that oscillates around zero, with the indicator also calculating a 20-period standard deviation of the score to measure volatility. This approach creates a data-driven sentiment gauge that quantifies the overall technical health of the reference market by mathematically weighting the importance of each technical factor based on historical relationships.
[DEM] Multi-Symbol Relative Strength Index Multi-Symbol Relative Strength Index is a comparative analysis indicator that simultaneously displays RSI values for five different symbols (defaulting to major tech stocks NVDA, MSFT, AAPL, AMZN, and GOOG) on a single chart pane. The indicator plots each symbol's RSI as colored lines with standard overbought (70) and oversold (30) reference levels, allowing traders to quickly compare relative momentum across multiple assets. A key feature is the dynamic background coloring that highlights which symbol currently has the extreme RSI value (either highest or lowest, depending on user selection), making it easy to identify which stock is showing the most extreme momentum condition at any given time. The indicator includes a legend table displaying all tracked symbols with their corresponding colors, and the background fill between the 30-70 RSI levels provides clear visual reference for overbought and oversold zones across all symbols simultaneously.
[DEM] Multi-RSI Signal (With Backtesting) Multi-RSI Signal (With Backtesting) is a technical indicator that generates buy signals based on multiple RSI (Relative Strength Index) timeframes simultaneously reaching oversold conditions. The indicator monitors RSI values across seven different periods (2, 3, 4, 5, 6, 8, 25, 50, and 100) and triggers a buy signal only when all shorter-term RSIs (2-8 periods) drop below specific thresholds (mostly below 10-20) while longer-term RSIs (25, 50, 100) remain within defined ranges, indicating a confluence of oversold conditions across multiple timeframes. The system includes comprehensive backtesting capabilities that track signal accuracy, average returns, and signal frequency over time, displaying these performance metrics in a real-time statistics table. Unlike typical single-RSI approaches, this multi-timeframe methodology aims to filter out false signals by requiring alignment across various RSI periods, though it currently only generates buy signals with no corresponding sell signal logic implemented.
[DEM] Momentum Bars Momentum Bars is designed to color price bars based on a combination of Aroon oscillator analysis and RSI momentum to identify periods of strong directional bias and filter out choppy or indecisive market conditions. The indicator calculates the Aroon Up and Aroon Down values over a configurable period (default 20) to determine which direction has more recent strength, then combines this with RSI analysis using the same period to confirm momentum alignment. Bars are colored green when Aroon Up exceeds Aroon Down (indicating recent highs dominate) and RSI is above 50 (confirming bullish momentum), red when Aroon Down exceeds Aroon Up (indicating recent lows dominate) and RSI is below 50 (confirming bearish momentum), and purple for all other conditions where the Aroon and RSI signals are conflicting or neutral, providing traders with immediate visual feedback about when price momentum and recent high/low activity are aligned versus when market conditions are mixed.
Information Flow Analysis[b🔄 Information Flow Analysis: Systematic Multi-Component Market Analysis Framework
SYSTEM OVERVIEW AND ANALYTICAL FOUNDATION
The Information Flow Kernel - Hybrid combines established technical analysis methods into a unified analytical framework. This indicator systematically processes three distinct data streams - directional price momentum, volume-weighted pressure dynamics, and intrabar development patterns - integrating them through weighted mathematical fusion to produce statistically normalized market flow measurements.
COMPREHENSIVE MATHEMATICAL FRAMEWORK
Component 1: Directional Flow Analysis
The directional component analyzes price momentum through three mathematical vectors:
Price Vector: p = C - O (intrabar directional bias)
Momentum Vector: m = C_t - C_{t-1} (bar-to-bar velocity)
Acceleration Vector: a = m_t - m_{t-1} (momentum rate of change)
Directional Signal Integration:
S_d = \text{sgn}(p) \cdot |p| + \text{sgn}(m) \cdot |m| \cdot 0.6 + \text{sgn}(a) \cdot |a| \cdot 0.3
The signum function preserves directional information while absolute values provide magnitude weighting. Coefficients create a hierarchy emphasizing intrabar movement (100%), momentum (60%), and acceleration (30%).
Final Directional Output: K_1 = S_d \cdot w_d where w_d is the directional weight parameter.
Component 2: Volume-Weighted Pressure Analysis
Volume Normalization: r_v = \frac{V_t}{\overline{V_n}} where \overline{V_n} represents the n-period simple moving average of volume.
Base Pressure Calculation: P_{base} = \Delta C \cdot r_v \cdot w_v where \Delta C = C_t - C_{t-1} and w_v is the velocity weighting factor.
Volume Confirmation Function:
f(r_v) = \begin{cases}
1.4 & \text{if } r_v > 1.2 \
0.7 & \text{if } r_v < 0.8 \
1.0 & \text{otherwise}
\end{cases}
Final Pressure Output: K_2 = P_{base} \cdot f(r_v)
Component 3: Intrabar Development Analysis
Bar Position Calculation: B = \frac{C - L}{H - L} when H - L > 0 , else B = 0.5
Development Signal Function:
S_{dev} = \begin{cases}
2(B - 0.5) & \text{if } B > 0.6 \text{ or } B < 0.4 \
0 & \text{if } 0.4 \leq B \leq 0.6
\end{cases}
Final Development Output: K_3 = S_{dev} \cdot 0.4
Master Integration and Statistical Normalization
Weighted Component Fusion: F_{raw} = 0.5K_1 + 0.35K_2 + 0.15K_3
Sensitivity Scaling: F_{master} = F_{raw} \cdot s where s is the sensitivity parameter.
Statistical Normalization Process:
Rolling Mean: \mu_F = \frac{1}{n}\sum_{i=0}^{n-1} F_{master,t-i}
Rolling Standard Deviation: \sigma_F = \sqrt{\frac{1}{n}\sum_{i=0}^{n-1} (F_{master,t-i} - \mu_F)^2}
Z-Score Computation: z = \frac{F_{master} - \mu_F}{\sigma_F}
Boundary Enforcement: z_{bounded} = \max(-3, \min(3, z))
Final Normalization: N = \frac{z_{bounded}}{3}
Flow Metrics Calculation:
Intensity: I = |z|
Strength Percentage: S = \min(100, I \times 33.33)
Extreme Detection: \text{Extreme} = I > 2.0
DETAILED INPUT PARAMETER SPECIFICATIONS
Sensitivity (0.1 - 3.0, Default: 1.0)
Global amplification multiplier applied to the master flow calculation. Functions as: F_{master} = F_{raw} \cdot s
Low Settings (0.1 - 0.5): Enhanced precision for subtle market movements. Optimal for low-volatility environments, scalping strategies, and early detection of minor directional shifts. Increases responsiveness but may amplify noise.
Moderate Settings (0.6 - 1.2): Balanced sensitivity for standard market conditions across multiple timeframes.
High Settings (1.3 - 3.0): Reduced sensitivity to minor fluctuations while emphasizing significant flow changes. Ideal for high-volatility assets, trending markets, and longer timeframes.
Directional Weighting (0.1 - 1.0, Default: 0.7)
Controls emphasis on price direction versus volume and positioning factors. Applied as: K_{1,weighted} = K_1 \times w_d
Lower Values (0.1 - 0.4): Reduces directional bias, favoring volume-confirmed moves. Optimal for ranging markets where momentum may generate false signals.
Higher Values (0.7 - 1.0): Amplifies directional signals from price vectors and acceleration. Ideal for trending conditions where directional momentum drives price action.
Velocity Weighting (0.1 - 1.0, Default: 0.6)
Scales volume-confirmed price change impact. Applied in: P_{base} = \Delta C \times r_v \times w_v
Lower Values (0.1 - 0.4): Dampens volume spike influence, focusing on sustained pressure patterns. Suitable for illiquid assets or news-sensitive markets.
Higher Values (0.8 - 1.0): Amplifies high-volume directional moves. Optimal for liquid markets where volume provides reliable confirmation.
Volume Length (3 - 20, Default: 5)
Defines lookback period for volume averaging: \overline{V_n} = \frac{1}{n}\sum_{i=0}^{n-1} V_{t-i}
Short Periods (3 - 7): Responsive to recent volume shifts, excellent for intraday analysis.
Long Periods (13 - 20): Smoother averaging, better for swing trading and higher timeframes.
DASHBOARD SYSTEM
Primary Flow Gauge
Bilaterally symmetric visualization displaying normalized flow direction and intensity:
Segment Calculation: n_{active} = \lfloor |N| \times 15 \rfloor
Left Fill: Bearish flow when N < -0.01
Right Fill: Bullish flow when N > 0.01
Neutral Display: Empty segments when |N| \leq 0.01
Visual Style Options:
Matrix: Digital blocks (▰/▱) for quantitative precision
Wave: Progressive patterns (▁▂▃▄▅▆▇█) showing flow buildup
Dots: LED-style indicators (●/○) with intensity scaling
Blocks: Modern squares (■/□) for professional appearance
Pulse: Progressive markers (⎯ to █) emphasizing intensity buildup
Flow Intensity Visualization
30-segment horizontal bar graph with mathematical fill logic:
Segment Fill: For i \in : filled if \frac{i}{29} \leq \frac{S}{100}
Color Coding System:
Orange (S > 66%): High intensity, strong directional conviction
Cyan (33% ≤ S ≤ 66%): Moderate intensity, developing bias
White (S < 33%): Low intensity, neutral conditions
Extreme Detection Indicators
Circular markers flanking the gauge with state-dependent illumination:
Activation: I > 2.0 \land |N| > 0.3
Bright Yellow: Active extreme conditions
Dim Yellow: Normal conditions
Metrics Display
Balance Value: Raw master flow output ( F_{master} ) showing absolute directional pressure
Z-Score Value: Statistical deviation ( z_{bounded} ) indicating historical context
Dynamic Narrative System
Context-sensitive interpretation based on mathematical thresholds:
Extreme Flow: I > 2.0 \land |N| > 0.6
Moderate Flow: 0.3 < |N| \leq 0.6
High Volatility: S > 50 \land |N| \leq 0.3
Neutral State: S \leq 50 \land |N| \leq 0.3
ALERT SYSTEM SPECIFICATIONS
Mathematical Trigger Conditions:
Extreme Bullish: I > 2.0 \land N > 0.6
Extreme Bearish: I > 2.0 \land N < -0.6
High Intensity: S > 80
Bullish Shift: N_t > 0.3 \land N_{t-1} \leq 0.3
Bearish Shift: N_t < -0.3 \land N_{t-1} \geq -0.3
TECHNICAL IMPLEMENTATION AND PERFORMANCE
Computational Architecture
The system employs efficient calculation methods minimizing processing overhead:
Single-pass mathematical operations for all components
Conditional visual rendering (executed only on final bar)
Optimized array operations using direct calculations
Real-Time Processing
The indicator updates continuously during bar formation, providing immediate feedback on changing market conditions. Statistical normalization ensures consistent interpretation across varying market regimes.
Market Applicability
Optimal performance in liquid markets with consistent volume patterns. May require parameter adjustment for:
Low-volume or after-hours sessions
News-driven market conditions
Highly volatile cryptocurrency markets
Ranging versus trending market environments
PRACTICAL APPLICATION FRAMEWORK
Market State Classification
This indicator functions as a comprehensive market condition assessment tool providing:
Trend Analysis: High intensity readings ( S > 66% ) with sustained directional bias indicate strong trending conditions suitable for momentum strategies.
Reversal Detection: Extreme readings ( I > 2.0 ) at key technical levels may signal potential trend exhaustion or reversal points.
Range Identification: Low intensity with neutral flow ( S < 33%, |N| < 0.3 ) suggests ranging market conditions suitable for mean reversion strategies.
Volatility Assessment: High intensity without clear directional bias indicates elevated volatility with conflicting pressures.
Integration with Trading Systems
The normalized output range facilitates integration with automated trading systems and position sizing algorithms. The statistical basis provides consistent interpretation across different market conditions and asset classes.
LIMITATIONS AND CONSIDERATIONS
This indicator combines established technical analysis methods and processes historical data without predicting future price movements. The system performs optimally in liquid markets with consistent volume patterns and may produce false signals in thin trading conditions or during news-driven market events. This indicator is provided for educational and analytical purposes only and does not constitute financial advice. Users should combine this analysis with proper risk management, position sizing, and additional confirmation methods before making any trading decisions. Past performance does not guarantee future results.
Note: The term "kernel" in this context refers to modular calculation components rather than mathematical kernel functions in the formal computational sense.
As quantitative analyst Ralph Vince noted: "The essence of successful trading lies not in predicting market direction, but in the systematic processing of market information and the disciplined management of probability distributions."
— Dskyz, Trade with insight. Trade with anticipation.
[DEM] Confirmation Signal (With Backtesting) Confirmation Signal (With Backtesting) is designed to generate buy and sell signals by combining Aroon oscillator analysis with Parabolic SAR positioning, smoothed EMA trend confirmation, and RSI filtering to create high-confidence trading opportunities. It also includes a comprehensive backtesting framework to evaluate the historical performance of these signals. The indicator overlays directly on the price chart, plotting signals and displaying performance statistics in a table while also coloring bars based on market conditions (green for bullish confirmation, red for bearish confirmation, purple for neutral). The strategy generates buy signals when the Aroon Up reaches 100% (new highs) combined with bullish trend confirmations, proper SAR positioning, RSI filters, and adequate time spacing between signals, while sell signals are triggered under opposite conditions, emphasizing signal quality over quantity through multiple confirmation layers and integrated backtesting metrics.
[DEM] Combo Signal (With Backtesting) Combo Signal (With Backtesting) is designed to generate buy and sell signals by combining seven different trading strategies that incorporate multiple technical indicators including SuperTrend, Parabolic SAR, MACD, and RSI. It also includes a comprehensive backtesting framework to evaluate the historical performance of these signals. The indicator overlays directly on the price chart, plotting signals and displaying performance statistics in a table. The strategy triggers buy signals when any of seven long conditions are met (including ATR-based reversal patterns, SuperTrend confirmations, RSI oversold crossovers, MACD bullish crossovers, and SuperTrend line breaks), while sell signals are generated when any of the corresponding seven short conditions occur, creating a multi-faceted approach that aims to capture various market conditions and trading opportunities while tracking signal accuracy, average returns, and signal frequency through its integrated backtesting system.
[Futures OI vs Price Change] (% Change)╔═══════════════════ RUBIXCUBE ══════════════════════╗
This indicator analyses the relationship between Open Interest percentage changes and price percentage changes in futures markets. Inspired by Checkonchain's market structure analysis, it displays this data as coloured column bars to identify different market conditions.
What This Indicator Shows
The indicator plots Open Interest percentage change as column bars, with colours representing four market regimes:
- Blue (Leveraged Rally): OI increases + Price increases (New leveraged long positions)
- Green (Spot Rally): OI decreases + Price increases (Organic buying or short covering)
- Orange (Leveraged Sell-Off): OI increases + Price decreases (New short positions or long liquidations)
- Red (Deleveraging Sell-Off): OI decreases + Price decreases (Position unwinding)
Bar transparency changes based on price movement magnitude. Larger price changes result in more solid bars, while smaller moves appear more transparent.
Data Sources
Aggregated Open Interest data from multiple exchanges:
- Binance USDT, USD & BUSD Perpetuals
- BitMEX USD & USDT Perpetuals
- Kraken USD Perpetuals
Settings
- OI % Change SMA: Smoothing period for Open Interest changes (Default: 7)
- Price % Change SMA: Smoothing period for price changes (Default: 7)
- Base Transparency: Baseline transparency level (0-100)
- Transparency Sensitivity: How much price change affects bar transparency
- Exchange Toggles: Enable/disable individual exchange data
Usage
This indicator helps identify market structure by showing whether price moves are accompanied by increasing or decreasing leveraged positions. Blue and orange bars indicate new leverage entering the market, while green and red bars suggest position reduction or organic spot activity.
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RSI Trend Navigator [QuantAlgo]🟢 Overview
The RSI Trend Navigator integrates RSI momentum calculations with adaptive exponential moving averages and ATR-based volatility bands to generate trend-following signals. The indicator applies variable smoothing coefficients based on RSI readings and incorporates normalized momentum adjustments to position a trend line that responds to both price action and underlying momentum conditions.
🟢 How It Works
The indicator begins by calculating and smoothing the RSI to reduce short-term fluctuations while preserving momentum information:
rsiValue = ta.rsi(source, rsiPeriod)
smoothedRSI = ta.ema(rsiValue, rsiSmoothing)
normalizedRSI = (smoothedRSI - 50) / 50
It then creates an adaptive smoothing coefficient that varies based on RSI positioning relative to the midpoint:
adaptiveAlpha = smoothedRSI > 50 ? 2.0 / (trendPeriod * 0.5 + 1) : 2.0 / (trendPeriod * 1.5 + 1)
This coefficient drives an adaptive trend calculation that responds more quickly when RSI indicates bullish momentum and more slowly during bearish conditions:
var float adaptiveTrend = source
adaptiveTrend := adaptiveAlpha * source + (1 - adaptiveAlpha) * nz(adaptiveTrend , source)
The normalized RSI values are converted into price-based adjustments using ATR for volatility scaling:
rsiAdjustment = normalizedRSI * ta.atr(14) * sensitivity
rsiTrendValue = adaptiveTrend + rsiAdjustment
ATR-based bands are constructed around this RSI-adjusted trend value to create dynamic boundaries that constrain trend line positioning:
atr = ta.atr(atrPeriod)
deviation = atr * atrMultiplier
upperBound = rsiTrendValue + deviation
lowerBound = rsiTrendValue - deviation
The trend line positioning uses these band constraints to determine its final value:
if upperBound < trendLine
trendLine := upperBound
if lowerBound > trendLine
trendLine := lowerBound
Signal generation occurs through directional comparison of the trend line against its previous value to establish bullish and bearish states:
trendUp = trendLine > trendLine
trendDown = trendLine < trendLine
if trendUp
isBullish := true
isBearish := false
else if trendDown
isBullish := false
isBearish := true
The final output colors the trend line green during bullish states and red during bearish states, creating visual buy/long and sell/short opportunity signals based on the combined RSI momentum and volatility-adjusted trend positioning.
🟢 Signal Interpretation
Rising Trend Line (Green): Indicates upward momentum where RSI influence and adaptive smoothing favor continued price advancement = Potential buy/long positions
Declining Trend Line (Red): Indicates downward momentum where RSI influence and adaptive smoothing favor continued price decline = Potential sell/short positions
Flattening Trend Lines: Occur when momentum weakens and the trend line slope approaches neutral, suggesting potential consolidation before the next move
Built-in Alert System: Automated notifications trigger when bullish or bearish states change, sending "RSI Trend Bullish Signal" or "RSI Trend Bearish Signal" messages for timely entry/exit
Color Bar Candles Option: Optional candle coloring feature that applies the same green/red trend colors to price bars, providing additional visual confirmation of the current trend direction
ma btc Multiple MA Convergence Alertbtc and eth ma15 20 50 200if converge
alert("EMA15, MA20, MA50, MA200 are converging/overlap crossing!", alert.freq_once_per_bar_close)
WaveTrend OscillatorWave trend Oscillator, similar to the other Cypher Oscillators, just that this oscillator is a little bit more refined less noise and a few better options for the money flow, but keeping the basic Structures and features. The only feature this does not have is the divergences
NK-Macd + Rsi3Here in one table you can see the MACD of the different time frame that what is the status of the MACD, is it above zero line or below zero line.
Second you will see in table that RSI number of all time frame, so here we dont need to go and check RSI by switching the chart and time frame.
at one place you will see both RSI and MACD, and by seeing the number you can check when the price in oversold zone and when it will in overbought also you can see the when the price in momentum and when not.
Example :- let assume RSI table showing above 40 in 1 hr and 67 in daily that means RSI is in swing momentum in hrly but momentum in daily.
LCS DynamicUses adaptive calculations to generate signals each signal has different rules to trade which will be updated shortly
Triple-Timeframe Stochastic Alerts (Smart Filtered)multi time stochastic w/ volume.
Smart filters, volume cool off,
3 adjustable time stochastic.
volume filter
Williams %R smoothed🌍 English Description
Williams %R Smoothed – by Ján Salma
This is the first smoothed version of the Williams %R indicator published on TradingView.
The traditional Williams %R is a momentum oscillator that can be very choppy and noisy. Many traders find it hard to use because of the constant whipsaws.
This indicator solves that problem by applying an EMA smoothing on top of the raw Williams %R values.
Why is this special?
[* ]📉 Reduces noise → much cleaner signal, fewer false spikes.
🔍 Highlights real momentum shifts → easier to spot when the market truly changes direction.
🎯 Customizable smoothing → you decide how sensitive or smooth the curve should be.
⚡ Unique → currently, there is no other smoothed Williams %R available on TradingView.
Settings
Length → default 14 (standard Williams %R period).
Smoothing → default 3 EMA (smooths out the raw values).
Levels: -20 (overbought), -80 (oversold), -50 (mid-level).
This indicator is great for scalpers and swing traders who love Williams %R but hate the noise.
Now you can finally use %R with more confidence and clarity.
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Slovenský popis
Williams %R Smoothed – od Jána Salmu
Toto je prvá vyhladená verzia Williams %R indikátora publikovaná na TradingView.
Klasický Williams %R je oscilátor hybnosti, ktorý je často veľmi „roztrasený“ a plný šumu. Mnoho traderov s ním preto pracuje ťažko, pretože dáva veľa falošných signálov.
Tento indikátor to rieši tak, že na pôvodné hodnoty Williams %R aplikuje EMA vyhladenie .
Čo robí tento indikátor výnimočným?
📉 Redukuje šum → výsledná krivka je čistejšia, s menej falošnými výkyvmi.
🔍 Zvýrazňuje skutočné zmeny hybnosti → jasnejšie vidíš, kedy sa trh naozaj otáča.
🎯 Nastaviteľné vyhladenie → citlivosť indikátora si prispôsobíš podľa seba.
⚡ Unikát → na TradingView zatiaľ neexistuje žiadny iný vyhladený Williams %R.
Nastavenia
Dĺžka → predvolená hodnota 14 (štandardný Williams %R).
Smoothing (EMA) → predvolená hodnota 3 (vyhladenie krivky).
Úrovne: -20 (prekúpený trh), -80 (prepredaný trh), -50 (stredová hodnota).
Tento indikátor je skvelý pre scalperov aj swing traderov, ktorí majú radi Williams %R, ale chcú ho používať s väčšou presnosťou a prehľadnosťou.
LRSlope - Linear Regression SlopeThis indicator attempts to predict the direction of the trend using least squares moving averages (LSMA).
The indicator's core purpose is to determine whether the price trajectory has a positive or negative slope and calculate directional changes. It also measures the strength of price momentum by calculating how strongly the slope.
The indicator calculates the slope of the curve for each bar and the EMA of these slopes for the specified period (Curve Length). It is consists of a histogram and two lines named "Average Slope"(white line) and "Simple" (green line).
The "Average Slope" is the simple moving average of the calculated EMA values.
" Simple " is SMA of calculated slopes.
The color of the histogram changes depending on the relative position of these two lines and zero line.
Simply put, the green bars of the histogram indicate an uptrend, blue bars indicate a horizontal or reverse movement, and red bars indicate a downtrend.
It is possible to see the strength of the momentum by the amount of change in the " Simple" (green line).
PowerDelta Oscillator [FxScripts]PowerDelta Oscillator
The PowerDelta Oscillator measures real-time buying and selling pressure using the proprietary PowerDelta Algorithm. By quantifying order flow, it identifies whether the market conditions favor bullish or bearish activity, helping traders determine directional bias for both trend and countertrend setups.
Calculation Methodology
The PowerDelta computes the delta (difference) between buying and selling pressure by integrating both price movement and volume behavior rather than relying solely on volume or price-based approximations like other oscillators.
The PowerDelta Algorithm evaluates six core price-volume conditions:
Price advancing with increasing volume
Price advancing with decreasing volume
Price consolidating with increasing volume
Price consolidating with decreasing volume
Price declining with increasing volume
Price declining with decreasing volume
From these conditions, the algorithm derives:
Accumulation vs Distribution phases
Buyer/Seller exhaustion points
Effort vs No Result scenarios (volume pressure failing to move price)
Operational Use
The PowerDelta Oscillator has three operational modes:
Trend
Countertrend
Blended (Trend/Countertrend hybrid)
Trend Mode
In Trend Mode, the indicator plots an oscillator that fluctuates between positive and negative values:
Positive readings indicate dominant buying pressure
Negative readings indicate dominant selling pressure
The magnitude of the reading reflects the intensity of the pressure
Crossovers at the zero line provide directional shifts:
Negative → Positive: bullish transition
Positive → Negative: bearish transition
Additionally:
Sustained positive values indicate control by buyers, long bias is favoured
Sustained negative values indicate control by sellers, short bias is favoured
The magnitude of displacement from zero provides additional confirmation of market strength or weakness
Countertrend Mode
In Countertrend Mode, the primary use of the PowerDelta Oscillator is to locate divergences between price and the oscillator (as visualised on the chart above) which helps traders pinpoint potential reversals
The oscillator is much more sensitive in this mode, making highs, lows and hence divergences, easier to spot
Like Trend Mode, the magnitude of displacement from zero provides additional confirmation of market strength or weakness
The various Analytical Scenarios detailed below provide detailed use cases for both Trend and Countertrend Mode
Blended Mode
To provide maximum flexibility, there’s also a third Blended Mode
This mode combines elements of the two primary modes and can be used as part of a hybrid approach making it easier to spot both trends and reversals
Alternative Source
The PowerDelta algorithm utilises volume data therefore it’s best to use the most reliable source of volume data for the instrument being traded
For instance, whilst XAUUSD provides excellent results with most forex brokers, slightly better results may be achieved using GC futures data which comes direct from the exchange (data package required)
To use a third-party source, select 'Alternative' and input the relevant source
This can also be used as a way to monitor correlated pairs by adding two instances of the PowerDelta to the same chart, selecting pair 1 e.g. EURUSD as the first instance and the correlated pair e.g. USDCHF as the second instance
Thorough backtesting advised
Analytical Scenarios
Accumulation: High positive oscillator readings combined with upward price movement suggest active accumulation.
Optimal strategy: Monitor pullbacks for potential long entries or wait for a divergence with price and potential reversal.
Distribution: High negative oscillator readings with downward price movement indicate distribution.
Optimal strategy: Monitor pullbacks for potential short entries or wait for a divergence with price and potential reversal.
Buyer Exhaustion: Price forms higher highs while oscillator value declines. Indicates weakening buying strength and potential bearish reversal.
Seller Exhaustion: Price forms lower lows while oscillator value contracts. Indicates weakening selling strength and potential bullish reversal.
Effort / No Result (Buyers): Positive oscillator expansion without higher highs indicates aggressive buying without price confirmation, suggesting overbought conditions and a potential bearish reversal.
Effort / No Result (Sellers): Negative oscillator expansion without lower lows indicates aggressive selling without price confirmation, suggesting oversold conditions and a potential bullish reversal.
Alerts
To trigger alerts when market bias transitions across the zero line:
Right-click on chart → Add Alert on PowerDelta
Condition: PowerDelta → Select Mode
Type: Crossing
Value: 0
Execution: Once Per Bar Close
Adjust additional parameters as required
Performance and Optimization
Backtesting Results: The PowerDelta Oscillator has undergone extensive backtesting across various instruments, timeframes and market conditions, demonstrating strong performance in identifying strong trends and reversals. User backtesting is strongly encouraged as it allows traders to optimize settings for their preferred instruments and timeframes.
Optimization for Diverse Markets: The PowerDelta Oscillator can be used on crypto, forex, indices, commodities and stocks. The PowerDelta Oscillator's algorithmic foundation ensures consistent performance across a variety of instruments. The Trend, Countertrend and Blended Modes make it easy for the trader to set up based on their individual trading style.
Educational Resources and Support
Users of the PowerDelta Oscillator benefit from comprehensive educational resources and full access to FxScripts Support. This ensures traders can maximize the potential of the PowerDelta Oscillator and other tools in the Sigma Indicator Suite by learning best practices and gaining insights from an experienced team of traders.
Supertrend Channel Histogram OscillatorThis histogram is based on the script "Supertrend Channels "
The idea of the indicator is to visually represent the interaction of price with several different supertrend channels of various lengths in an oscillator in order to make it much more clear to the trader how the longer trends are interacting with shorter trends of the price movement of an asset. I got this idea from the "Kurutoga Cloud" and "Kurutoga Histogram" by D7R which is based on the centerlines of 3 Donchian Channels, however after I started using the Supertrend Channel by LuxAlgo I found that it was a more reliable price range channel than a standard Donchian Channel and I made this indicator to accompany it.
This indicator plots a positive value above 0 when the price is above the centerline of the supertrend channel and a negative value below 0 when the price is below the centerline.
The first supertrend's length and multiple can be adjusted in the settings.
The given supertrend input is then doubled and quadrupled in both length and multiplication so that a supertrend histogram with the values of 3, 3 will be accompanied by 2 additional supertrend histograms with the values of 6, 6 and 12, 12.
The larger price trend histograms are clearly visible behind the short term supertrend channel's histogram, giving traders a balanced view of short and long term trends interacting. The less visible columns of the larger trend remain above or below the 0 line behind the more visible short term channel trend, helping to spot pullbacks within a larger trend.
Additionally, when the 3 separate histograms are all positive or all negative but the histogram columns are separating from each other this can indicate a potential trend exhaustion leading to reversal or pullback about to happen.
The overbought and oversold lines at 50 and -50 are representative primarily of the short term trend with above 50 or below -50 indicating that the price is pushing the boundary and potentially beginning a new short term supertrend in the opposite direction. If values do not noticably exceed these levels, then the current short term trend movement can be viewed as a pullback within a larger trend, with continuation potentially to follow.
I have had troubles converting the original code to v6 so this will be published here in v5 of pinescript to be used in conjunction with the original. I was intending to create a companion indicator for this oscillator that represents 3 supertrends with corresponding 2x and 4x calculations based on LuxAlgo's script, but I can't seem to get it to work correctly in v5.
For best visualization of the trends 3 LuxAlgo Supertrend channels with 2x and 4x values should be used in conjunction with each other to fully visualize the histogram.
Used in conjunction with other indicators this can be a very effective strategy to capture larger trend moves and pullbacks within trends, as well as warn of potential price trend exhaustion.
